FARA: A Fast Artifact Recovery Algorithm with Optimum Stimulation Waveform for Single-Cell Resolution Massively Parallel Neural Interfaces

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Abstract

This paper introduces a fast artifact recovery algorithm (FARA) that uses electrochemical impedance spectroscopy to model the electrode-tissue interface and design an optimum stimulation waveform to minimize the residual artifact duration in single-cell resolution neural interfaces. Results in saline solution with a custom PCB and a 30 $\mu \mathrm{m}$ diameter microelectrode array show a worst case artifact recovery time of 160 $\mu \mathrm{s}$ when measured from the end of the working phase (anodic 500 $\mathrm{n}\mathrm{A}, 250\mu \mathrm{s})$. On average, the proposed algorithm provides an 81% improvement over a triphasic charge-balanced stimulation waveform.
Original languageEnglish
Title of host publicationProceedings of the 2022 IEEE International Symposium on Circuits and Systems (ISCAS)
Place of PublicationDanvers
PublisherIEEE
Pages190-194
Number of pages5
ISBN (Electronic)978-1-6654-8485-5
ISBN (Print)978-1-6654-8486-2
DOIs
Publication statusPublished - 2022
Event2022 IEEE International Symposium on Circuits and Systems (ISCAS) - Austin, United States
Duration: 27 May 20221 Jun 2022

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume2022-May
ISSN (Print)0271-4310

Conference

Conference2022 IEEE International Symposium on Circuits and Systems (ISCAS)
Country/TerritoryUnited States
CityAustin
Period27/05/221/06/22

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care

Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

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